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COVID-19 and the judiciary: the case for access to testing Sudhi versus Union of India

2020· article· en· W3082123858 on OpenAlexaff
Diya Uberoi

Bibliographic record

VenueInternational Journal of Community Medicine and Public Health · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHuman Rights and Development
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsSupreme courtGovernment (linguistics)LawObligationState (computer science)Political scienceCoronavirus disease 2019 (COVID-19)Right to healthPovertyHealth carePublic administrationMedicine

Abstract

fetched live from OpenAlex

In an effort to protect citizens’ right-to-health, the Supreme Court of India on April 8th ordered the government to make COVID-19 testing free in all private hospitals and labs. The Court’s decision in Sudhi v. Union of India marked a significant step towards ensuring that all people, especially poor workers in the informal sector have access to necessary care. Five days later, however, after facing objections from private companies and the state, the Supreme Court reversed its previous order and made testing free for only those living below the poverty line, an obligation already mandated under the National Health Policy Scheme.This commentary suggests that judicial action should be strengthened, not hampered, in times of global health crisis. While no state has unlimited resources to ensure the protection of health, the judiciary should be emboldened to hold the state to account.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.730
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.419
GPT teacher head0.498
Teacher spread0.079 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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